Washington DC [US], December 27 (ANI): Plastic garbage and its accumulation in nature has recently become a major environmental concern. While plastic pollution in the oceans is undeniably a concern, the presence of plastics in soils all over the world is also known to cause serious environmental and health problems.
Plastics fragment into tiny particles known as microplastics (MPs) in the soil due to natural and anthropogenic processes, altering soil characteristics significantly. Furthermore, they are absorbed by plants, potentially entering the human food chain and creating health problems.
Understanding the impact of MPs on soil qualities is important for company sustainability, particularly in the ‘Environmental’ portion of Environmental, Social, and Governance (ESG) goals. Global firms are frequently challenged with rising pressure to adopt eco-friendly practices, with a particular emphasis on dealing with plastic-related issues at the heart of these projects.
However, the underlying mechanisms governing soil MPs’ environmental influence are still unknown. Because of soil heterogeneity and MP diversity, soil-MP interactions are complicated, making prediction and mitigation of their impacts on soil parameters difficult.
To address this gap in soil MP research, a group of scientists led by Prof. Yong Sik Ok employed machine learning (ML) algorithms to assess and forecast the influence of MPs on soil parameters.
Prof. Ok is a KU HCR Professor, President of the International ESG (Environmental, Social, and Governance) Association (IESGA), and Chair and Programme Director of the Association of Pacific Rim Universities’ Sustainable Waste Management Programme (APRU SWM Programme).
“ML is a dynamic and transformative field of artificial intelligence (AI) that uses algorithms and models to learn and make predictions from vast datasets with great accuracy. Using ML to comprehensively understand the role of MPs in soil systems is time- and resource-efficient and provides a foundation for future research on this subject,” explained Prof. Ok, the corresponding author of this study.
The results of their study were made available online on 5 November 2023 in Environmental Pollution, following Prof. Ok’s two critical reviews published under the collection ‘Plastics in the Environment’ in Nature Reviews Earth and Environment, a journal by Nature.
The ML algorithms were programmed to predict the influence of MPs on soil properties and found that different MP factors, such as type, size, shape, and dosage, significantly altered soil properties. Specifically, MP size was identified as a major factor that affects soil properties. Besides this, the shape, type, and dosage of MP were also found to distinctly influence the soils’ chemical properties.
“This pioneering study contributes essential data to support informed decision-making on plastic waste management, aligning with the global focus on sustainability and ESG principles. It underscores the importance of innovative research in guiding corporate sustainability efforts, where plastic-related issues are a growing concern. The application of ML techniques to this problem demonstrates the potential for advanced technology to drive sustainable practices and create a greener, more eco-conscious future,” said Prof. Ok.
These quantitative insights into the influence of MPs on soil characteristics represent a breakthrough in comprehending and mitigating the plastic waste dilemma. The study’s utilization of ML algorithms marks a groundbreaking shift from traditionally complex and resource-intensive methods for predicting and interpreting the impact of MPs on soil properties.
“Our ML-based approach for this study underscores the potential of advanced technology to address the challenge of MP pollution in our environment. Such data-driven research could guide informed decision-making on plastic waste management while aligning with global sustainability goals and the principles of ESG, social responsibility, and community engagement. Furthermore, this could revolutionize corporate sustainability efforts and pave the way for more green jobs and sustainable development to create a greener and eco-conscious world for current and future generations,” said Prof. Ok.
Integrating ML insights to study the impact of MPs in the context of ESG aligns with social responsibility, fostering sustainable practices with positive community effects. Corporations tackling MP pollution can not only reduce their environmental footprint but also build community trust by applying ML solutions. These efforts could, in turn, influence industry standards, potentially creating jobs and driving economic growth in related fields.
“We have consistently addressed global threats posed by plastic pollution and the importance of soil ecosystems, exemplified by our contributions of three articles to Nature Journals’ groundbreaking special issues on ‘Soils in Food Systems’ and ‘Plastics in the Environment’,” concluded Prof. Ok. (ANI)
